ATTENDANCE SYSTEM USING FACE RECOGNITION AND RASP BERRY PI–REVIEW

Abstract

The attendance process is currently done by hand. This results in significant time loss for both instructors and students. When attendance is manually recorded, pupils have to wait longer. Manual work is intimately associated with human error. The face of every individual is significant, identifiable evidence. As a result, automating the attendance process will extend classroom instruction. We chose the Raspberry Pi so that everyone could use face recognition. Traditional face detection and recognition techniques are used in a Raspberry Pi-based facial recognition system. Facial recognition is essential for surveillance and security. As a result, an economical and efficient method is required. The identification method is based on face recognition and is further divided into three steps: real-time detection, feature extraction and classification, and face recognition. Facial recognition is recognized as a critical phase in our system.currently The OpenCV library is used in Python to construct this system.